Searcharxiv⌕ Search

arXiv subjects

Yibin Feng

Publications and source records attributed to Yibin Feng.

9 recordsLinked to original sources
arXiv2026

Understanding and Supporting Online Discussion with Opinionated Chatbots

Opinionated chatbots are increasingly present on online platforms and have the potential to shape public discourse by influencing individuals' viewpoints before they engage in discussions. Despite their growing presence, the impact of interacting with opinionated chatbots on subsequent online interactions remains largely unexplored. This study investigated how exposure to different types of opinionated chatbots, specifically those expressing opposing, reinforcing, or balanced viewpoints, affected participants' subsequent online discussions. In a controlled experiment with 83 participants, we found that interacting with an opinionated chatbot that consistently opposed participants' arguments led to greater shifts in opinion, indicating enhanced openness to revising one's initial stance. Conversely, participants who interacted with a chatbot that consistently reinforced their views were more likely to adopt more agreeable communication styles in subsequent conversations with others. Furthermore, interactions with different types of opinionated chatbots resulted in varying levels of trust, as well as different perceptions of chatbots and human interlocutors. Our findings indicate that opinionated chatbots can influence both individuals' opinions on social topics and their communication behaviors in online environments. This presents a trade-off for future designers seeking to facilitate cognitive flexibility in changing opinions while maintaining positive user experiences and trust in the chatbots during public discourse. We discuss the implications for designing opinionated chatbots to promote more constructive and less polarized online

cs.HC↗
arXiv2026

Magnetoresistance Oscillations in Few-Layer NbSe2 in Superconducting Fluctuation Regime

Quantum interference phenomena in superconductors, such as Josephson interference and Little-Parks oscillations, serve as powerful probes of phase coherence, symmetry breaking and vortex dynamics. However, they are typically observed in well-defined mesoscopic structures, and their behavior in the two-dimensional limit remains largely unexplored. Here, we report periodic magnetoresistance oscillations, superconducting interference patterns, and interfering diode effect in unpatterned few-layer NbSe2. These phenomena emerge exclusively within the superconducting fluctuation regime of thin samples, consistent with the enhanced anomalous metallic behavior of atomically thin NbSe2. The non-monotonic temperature dependence of both the oscillation amplitude and the diode efficiency can be captured by a model in which thermally activated vortices traverse intrinsic supercurrent loops. Our results reveal that the observed interference phenomena originate from the lost of global phase coherence, providing a new route to accessing interference effects in unpatterned superconductors.

cond-mat.supr-con↗
arXiv2026

Multi-Agent Systems Shape Social Norms for Prosocial Behavior Change

Social norm interventions are used promote prosocial behaviors by highlighting prevalent actions, but their effectiveness is often limited in heterogeneous populations where shared understandings of desirable behaviors are lacking. This study explores whether multi-agent systems can establish "virtual social norms" to encourage donation behavior. We conducted an online experiment where participants interacted with a group of agents to discuss donation behaviors. Changes in perceived social norms, conformity, donation behavior, and user experience were measured pre- and postdiscussion. Results show that multi-agent interactions effectively increased perceived social norms and donation willingness. Notably, in-group agents led to stronger perceived social norms, higher conformity, and greater donation increases compared to out-group agents. Our findings demonstrate the potential of multi-agent systems for creating social norm interventions and offer insights into leveraging social identity dynamics to promote prosocial behavior in virtual environments.

cs.HC↗
arXiv2025

Multi-Agents are Social Groups: Investigating Social Influence of Multiple Agents in Human-Agent Interactions

Multi-agent systems - systems with multiple independent AI agents working together to achieve a common goal - are becoming increasingly prevalent in daily life. Drawing inspiration from the phenomenon of human group social influence, we investigate whether a group of AI agents can create social pressure on users to agree with them, potentially changing their stance on a topic. We conducted a study in which participants discussed social issues with either a single or multiple AI agents, and where the agents either agreed or disagreed with the user's stance on the topic. We found that conversing with multiple agents (holding conversation content constant) increased the social pressure felt by participants, and caused a greater shift in opinion towards the agents' stances on each topic. Our study shows the potential advantages of multi-agent systems over single-agent platforms in causing opinion change. We discuss design implications for possible multi-agent systems that promote social good, as well as the potential for malicious actors to use these systems to manipulate public opinion.

cs.AI↗
arXiv2025

Artificial intelligence in drug discovery: A comprehensive review with a case study on hyperuricemia, gout arthritis, and hyperuricemic nephropathy

This paper systematically reviews recent advances in artificial intelligence (AI), with a particular focus on machine learning (ML), across the entire drug discovery pipeline. Due to the inherent complexity, escalating costs, prolonged timelines, and high failure rates of traditional drug discovery methods, there is a critical need to comprehensively understand how AI/ML can be effectively integrated throughout the full process. Currently available literature reviews often narrowly focus on specific phases or methodologies, neglecting the dependence between key stages such as target identification, hit screening, and lead optimization. To bridge this gap, our review provides a detailed and holistic analysis of AI/ML applications across these core phases, highlighting significant methodological advances and their impacts at each stage. We further illustrate the practical impact of these techniques through an in-depth case study focused on hyperuricemia, gout arthritis, and hyperuricemic nephropathy, highlighting real-world successes in molecular target identification and therapeutic candidate discovery. Additionally, we discuss significant challenges facing AI/ML in drug discovery and outline promising future research directions. Ultimately, this review serves as an essential orientation for researchers aiming to leverage AI/ML to overcome existing bottlenecks and accelerate drug discovery.

cs.AI↗
arXiv2022

On the Lp Gaussian Minkowski problem

Existence of symmetric (resp. asymmetric) solutions to the $L_p$ Gaussian Minkowski problem for $p\leq 0$ (resp. $p\geq 1$) will be provided. Moreover, existence and uniqueness of smooth solutions to the problem for $p>n$ will also be proved without the restriction that the Gaussian volumes of convex bodies are not less than one-second.

math.AP↗
arXiv2022

A note on the singular set of the no-sign obstacle problem

In this note, we prove the uniqueness of blowups at singular points of the no-sign obstacle problem $Δu=χ_{_{B_1\backslash \{u=|Du|=0\}}}\ \text{in}\ B_1,$ thus give a positive answer to a problem raised in \cite[Notes of Chaper 7, page 149]{PSU12}.

math.AP↗
arXiv2022

Uniqueness of solutions to the logarithmic Minkowski problem in $\mathbb{R}^3$

In this paper, we prove the uniqueness of solutions to the logarithmic Minkowski problem in $\mathbb{R}^3$ without symmetry condition, provided the density of the measure is close to $1$ in $C^α$ norm. This result also implies the uniqueness of self-similar solutions to the anisotropic Gauss curvature flow in $\mathbb{R}^3$ when the speed function is $C^α$ close to a positive constant.

math.AP↗